metadata
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BBC_CLS_deberta_v3_large_v2
results: []
BBC_CLS_deberta_v3_large_v2
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0857
- Accuracy: 0.9866
- Precision: 0.9723
- Recall: 0.9780
- F1: 0.9751
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.235 | 1.0 | 66 | 0.6331 | 0.7964 | 0.4047 | 0.4873 | 0.4418 |
| 0.4336 | 2.0 | 132 | 0.2201 | 0.8971 | 0.6754 | 0.7091 | 0.6910 |
| 0.2133 | 3.0 | 198 | 0.0990 | 0.9776 | 0.9476 | 0.9786 | 0.9602 |
| 0.1083 | 4.0 | 264 | 0.1038 | 0.9821 | 0.9656 | 0.9651 | 0.9653 |
| 0.0848 | 5.0 | 330 | 0.0907 | 0.9866 | 0.9782 | 0.9714 | 0.9747 |
| 0.1087 | 6.0 | 396 | 0.1270 | 0.9799 | 0.9672 | 0.9689 | 0.9671 |
| 0.1011 | 7.0 | 462 | 0.1289 | 0.9754 | 0.9677 | 0.9660 | 0.9667 |
| 0.0827 | 8.0 | 528 | 0.0990 | 0.9799 | 0.9818 | 0.9479 | 0.9632 |
| 0.0621 | 9.0 | 594 | 0.0857 | 0.9866 | 0.9723 | 0.9780 | 0.9751 |
| 0.0444 | 10.0 | 660 | 0.1071 | 0.9843 | 0.9769 | 0.9663 | 0.9715 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 1.13.1
- Datasets 2.13.0
- Tokenizers 0.14.1